88-308 Human and Machine Decisions from Experience
9 units, Carnegie Mellon University
This course investigates the similarities and differences between human and machine cognition in the context of decisions from experience. Students will attain firsthand experience implementing psychological models of human cognition, as well as computational methods that have applications in cognitive science and machine learning. Programming assignments will be completed in the python programming language, previous experience with python is helpful but not required. A final project will afford students the opportunity to propose novel research, design their own learning model, or review and evaluate existing research. Topics include human and machine decision making based on utility, learning from experience, heuristics and biases, applications of cognitive models, cognitive neuroscience, and mathematical theories of decision making.
Prerequisites: 36-200 or 88-230 or 36-220 or 70-207 or 88-120 or 36-218 or 36-225
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